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  • How Margin Assurance helps telcos grow their Business

    How Margin Assurance helps telcos grow their Business

    Introduction

    Modern technologies and digital transformation are disrupting the existing business models for communication service providers (CSPs). With the breakneck speed of innovation CSPs are constantly investing in new technologies leading to escalating Capex and stiff competition from players like Over the Top (OTT) solution providers. With such dynamic ecosystems, flexible products, and increasing customer demand for digital services, it is challenging for CSPs to secure margins. Yet, they must keep pace with change to remain relevant in today’s competitive landscape. Telcos should focus on how these disruptions impact their bottom line and profitability. The need of the hour is robust margin assurance programs and solutions that enable data-driven decisions and strategic investments with greater RoI.

    Telecommunications – Fixed and Wireless

    Revenue Growth (local currency)

    S&P Global 2022, Telecommunication trendsSource: S&P Global 2022, Telecommunication trends

    Telco Revenue is Declining, but the Future Holds Promise.

    The traditional telecom operator is no longer an isolated entity in the market. They engage in multiple collaborations for audio, video, content, analytics, cloud solutions, etc., to cater to the various needs of different customer segments. The growth trajectory is undoubtedly promising, thanks to an ecosystem replete with diverse and lucrative partners. But, monitoring long-term profitability remains a concern.

    For instance, a 2022 global report by S&P predicts that CSP revenue growth will decline in 2023 compared to 2022. Several trends are steering this shift:

    • New Over-the-Top (OTT) players are eating into telecom revenues by offering a wide bouquet of customer-centric services at competitive prices.
    • Evolution of telecom technologies like 4G and LTE are depleting voice revenues while increasing demand and consumption of data services.
    • Business partnerships are now highly complex, and the lack of granular visibility into products and services leads to shrinking margins.
    Why do Telcos Struggle with Profitable Revenue Decisions?

    To retain their edge, telcos instituted changes in how they operate and what they offer customers. But these also affect revenues for the following reasons:

    1. Product complexity impacts profitability

    The primary offering from traditional telecom operators was voice and SMS services. But, as customer usage patterns become increasingly data-heavy, we see a shift towards consume-all-you-can packs. Moreover, to keep customers engaged, telcos need to do more. They have to offer apps, bundled OTT services, and intelligent offerings. It has created an intricate portfolio governed by complex product structures and multiple offerings, which are very hard to manage from a service delivery perspective. Significantly, executing smart pricing decisions and measuring profitability among these numerous and complex interactions is hard.

    2. OTT partnerships eat into telco margins

    Customer demand for OTT content – such as videos, music, movies, etc. – delivered through communication networks forces operators to enter into partnerships with OTT providers on local, regional, and global levels. Bundling such services is a competitive differentiator for telcos to retain and attract subscribers. However, margins are sometimes affected because telcos have limited ways of gauging whether the partnerships are, in truth, profitable and contributing to top-line growth. In some cases, these have low cost-benefit value, leading to partnerships with low profitability for telcos.

    3. New tech is Capex-heavy

    The pace of digital transformation has accelerated over the past five years, which puts pressure on telcos to upgrade their networks and adopt next-gen technologies such as automation, AI, network functions virtualization, etc. And while these initiatives bleed heavily into Capex budgets, many players are still unclear about actual RoI. Consider how network technologies took decades to evolve from 2G to 3G and then 4G. But moving from 4G to 5G is happening in just a few short years. These days, telcos are focusing more on metrics like average margin per user (AMPU) to get visibility into their service delivery stack rather than average revenue per user (ARPU), which is no longer an accurate indicator of profitability.

    Decoding the Power of Margin Assurance

    Margin Assurance is a comprehensive way for telecom operators to identify and measure direct and indirect costs in their balance sheet across operations, partnerships, customer services, and product/service offerings. It leverages analytics and automation to give business decision-makers visibility into revenue and margin KPIs, empowering smarter, strategic, and real-time decisions that effectively increase profitability.

    Here is a concise table mapping the capabilities of margin assurance to tangible business benefits for telcos:

    Areas Capabilities Benefits
    Operational efficiencies Maintains operational margins across costs plus essential margins as per industry best-practices Accurately derive, compute, and report on profitability
    Revenue KPIs Leverage AMPU to segment customers as profitable ones Enhance customer satisfaction by creating targeted campaigns
    Marketing & campaigns Devise strategies for cross-selling products based on customer segmentation Improve business decisions that result in higher revenue
    Partnership analytics Transparent margin analytics to channel resources into the right partnerships and customers Elevates productivity of telcos resources through insights into RoI of existing and new programs, products, and services
    Business intelligence Provides market intelligence and margin evaluation to understand one’s position against challenges based on subscriber behavior and margin trends Improves competitiveness through profitable pricing, unique margin products, and customer retention
    Sharpen Your Edge with Margin Assurance Best Practices

    Leveraging years of domain experience within the telecommunications industry, Subex has developed a powerful margin assurance solution that gives telcos granular insights into margins, revenue, and profitability. The three pillars of our solution approach are:

    • Robust cost allocation models, driven by best practices, whereby every cost line item is part of the P&L account
    • Advanced margin analytics that immediately identifies low-performing areas with simulation to determine how to boost performance along with intuitive dashboards for visualizing costs, insights, areas of action, and recommendations
    • Pioneering solution design that is exceptionally comprehensive across customers, products, segments, network levels, technologies, products, pricing, and more
    A Definitive Guide to Transform the Telco Business

    As a means to empower CSPs with the best practices when it comes to assuring margins, Subex has shared its approach in detail in the TMForum Guidebook titled ‘Business Assurance Transformation – Margin Assurance’, where we are the lead contributor along with other leading telecom operators and vendors. The guide examines how an approach that leverages automated cost allocation models for dynamic insights rather than static ones can drive better business decisions using next-gen technologies.

    Members can instantly download the TMForum guidebook here.

    To learn more about Subex’s approach to margin assurance.

    Read our white paper

  • Part 2: From Telcos to Tech-cos – Leapfrog to the Future with AI

    Part 2: From Telcos to Tech-cos – Leapfrog to the Future with AI

    In the 1960s, Xerox renewed its entire business model based on a single premise: Customers don’t want products. They want services. Having reached its tether’s end, the brand pivoted and is now one of the most successful providers of digital printing solutions. As Renee Montagne, the CEO of Xerox, in 2012 aptly stated, “If you don’t transform, you’re stuck.”

    Our touched on stories of AI and digital transformation. While traditionally slower to innovate than others, the telecom industry is waking up to the benefits of rapid digitalization, aggressive automation, and AI-led ecosystems.

    So, what’s next for telcos, and how do they leapfrog their AI programs? By transforming the entire operational process pipeline with AI at the core. Here are 5 ways to do this:

    1. Make AI Pervasive in Networks

    Software-defined networking (SDN) and network functions virtualization (NFV) help telcos rewire their networks dynamically for unprecedented gains. The applications rise beyond capacity planning and network management. For context, think of how replacing an appliance, like a ceiling fan, from a mechanical one to a smart fan alters user behavior as well as fan performance. Customers can download an app to start and stop the fan remotely, change its speed, monitor energy efficiency, and get recommendations for optimal settings. All of this is done remotely, delivering extreme user convenience. The seller, on the other hand, gets insights into performance to predict failures, diagnose issues, and preemptively schedule maintenance, saving on ad-hoc costs. Similarly, SDN facilitates a revolution in network provisioning and customer experience.

    2. Create AI-centric Business Models.

    More than providing infrastructure to run various innovative services, telcos must join the flurry of disruption by doing more with AI. One fundamental change is the ecosystem mindset that spawns new partnership models whereby telcos also grab a slice of the market thanks to their vast customer reach. As the saying goes, “Alone, I can run fast. Together, we can run far.” Telecom is ripe with examples of this. Consider how mobile wallets have bled into the FinTech space, nudging telcos into evaluating how they can offer solutions for fraud, encryption.

    3. Stay Agile with Open Architecture.

    An example in the previous blog illustrated how small shops can offer seamless customer onboarding. One of the levers is back-end data encryption for the digital verification of a customer’s credentials, which is impossible without open architecture. To simplify, one could compare open architecture to the standard-issue fuel inlet in all motor vehicles. No matter the automotive brand, all vehicles are outfitted with a single type of inlet valve, allowing the motorist to refill fuel at any fuel station. Similarly, the open architecture enables telcos to move away from proprietary software to those that grant fast, secure, and seamless interconnections to a larger ecosystem.

    Telcos can monetize data in resourceful ways, as in the case of alternate credit scoring using telecom data to support microfinance loans and creditworthiness to numerous non-banked populations where there is no conventional credit bureau. Open infrastructure and architecture equips telcos to wield innovations such as the movement towards Open RAN or the development of Open APIs by TMForum. It also streamlines collaborations among vendors so telcos can onboard partners and bundle services and packages with agility. Modern mobile apps of traditional telcos is a classic case, replete with non-telco services such as utility payments, mobile wallets, media and content, eCommerce, OTT subscriptions, and more.

    4. Strategize for AI-driven Sales, Channel, and Supply Chain Management.

    Indian insurance behemoth Life Insurance Corporation (LIC) set a precedent in how efficacious indirect channel marketing is when it empowered nearly 1.3 billion agents across India to sell its policies raking in nearly 96% of the titan’s revenues. Traditionally, telcos have not fully monetized indirect channels. With AI, this will change. Through cost-effective and seamless onboarding via digital apps and robust security protocols, AI can channelize visibility to new subscribers. For instance, when a customer books a flight ticket, telcos can promptly offer roaming plans customized to the subscriber based on their usage patterns. Similarly, AI can also revamp supply chain operations by infusing intelligent sourcing practices that respond intuitively to unpredictable market forces. The widespread impact on food supplies and other essential manufacturing raw materials due to unrest in Ukraine is a prime example of why diversified and intelligent supply chains are essential.

    5. Curate Frictionless Customer Experiences.

    Finally, all of this will bring to bear delightful customer experiences. As telcos use AI to reimagine their operations and processes, models and infrastructure, services, and products, it will have a game-changing impact on customers. Customers will not only experience first-hand the frictionless, delightful interactions crafted via AI but also cement their loyalty to a telecom provider that helps them live better lives and that prioritizes their conveniences and preferences – all in one single window.

    Imagine the opportunities. And now, reimagine them with AI.

    Subex is at the forefront of driving AI-led transformation. To watch a demo or learn how we help you revolutionize your business with AI, reach out to us at

    hypersense@subex.com

  • Part 2: From Telcos to Tech-cos – Leapfrog to the Future with AI

    In the 1960s, Xerox renewed its entire business model based on a single premise: Customers don’t want products. They want services. Having reached its tether’s end, the brand pivoted and is now one of the most successful providers of digital printing solutions. As Renee Montagne, the CEO of Xerox, in 2012 aptly stated, “If you don’t transform, you’re stuck.”

    Our touched on stories of AI and digital transformation. While traditionally slower to innovate than others, the telecom industry is waking up to the benefits of rapid digitalization, aggressive automation, and AI-led ecosystems.

    So, what’s next for telcos, and how do they leapfrog their AI programs? By transforming the entire operational process pipeline with AI at the core. Here are 5 ways to do this:

    1. Make AI Pervasive in Networks

    Software-defined networking (SDN) and network functions virtualization (NFV) help telcos rewire their networks dynamically for unprecedented gains. The applications rise beyond capacity planning and network management. For context, think of how replacing an appliance, like a ceiling fan, from a mechanical one to a smart fan alters user behavior as well as fan performance. Customers can download an app to start and stop the fan remotely, change its speed, monitor energy efficiency, and get recommendations for optimal settings. All of this is done remotely, delivering extreme user convenience. The seller, on the other hand, gets insights into performance to predict failures, diagnose issues, and preemptively schedule maintenance, saving on ad-hoc costs. Similarly, SDN facilitates a revolution in network provisioning and customer experience.

    2. Create AI-centric Business Models.

    More than providing infrastructure to run various innovative services, telcos must join the flurry of disruption by doing more with AI. One fundamental change is the ecosystem mindset that spawns new partnership models whereby telcos also grab a slice of the market thanks to their vast customer reach. As the saying goes, “Alone, I can run fast. Together, we can run far.” Telecom is ripe with examples of this. Consider how mobile wallets have bled into the FinTech space, nudging telcos into evaluating how they can offer solutions for fraud, encryption, and Anti-Money Laundering (AML).

    3. Stay Agile with Open Architecture.

    An example in the previous blog illustrated how small shops can offer seamless customer onboarding. One of the levers is back-end data encryption for the digital verification of a customer’s credentials, which is impossible without open architecture. To simplify, one could compare open architecture to the standard-issue fuel inlet in all motor vehicles. No matter the automotive brand, all vehicles are outfitted with a single type of inlet valve, allowing the motorist to refill fuel at any fuel station. Similarly, the open architecture enables telcos to move away from proprietary software to those that grant fast, secure, and seamless interconnections to a larger ecosystem.

    Telcos can monetize data in resourceful ways, as in the case of alternate credit scoring using telecom data to support microfinance loans and creditworthiness to numerous non-banked populations where there is no conventional credit bureau. Open infrastructure and architecture equips telcos to wield innovations such as the movement towards Open RAN or the development of Open APIs by TMForum. It also streamlines collaborations among vendors so telcos can onboard partners and bundle services and packages with agility. Modern mobile apps of traditional telcos is a classic case, replete with non-telco services such as utility payments, mobile wallets, media and content, eCommerce, OTT subscriptions, and more.

    4. Strategize for AI-driven Sales, Channel, and Supply Chain Management.

    Indian insurance behemoth Life Insurance Corporation (LIC) set a precedent in how efficacious indirect channel marketing is when it empowered nearly 1.3 billion agents across India to sell its policies raking in nearly 96% of the titan’s revenues. Traditionally, telcos have not fully monetized indirect channels. With AI, this will change. Through cost-effective and seamless onboarding via digital apps and robust security protocols, AI can channelize visibility to new subscribers. For instance, when a customer books a flight ticket, telcos can promptly offer roaming plans customized to the subscriber based on their usage patterns. Similarly, AI can also revamp supply chain operations by infusing intelligent sourcing practices that respond intuitively to unpredictable market forces. The widespread impact on food supplies and other essential manufacturing raw materials due to unrest in Ukraine is a prime example of why diversified and intelligent supply chains are essential.

    5. Curate Frictionless Customer Experiences.

    Finally, all of this will bring to bear delightful customer experiences. As telcos use AI to reimagine their operations and processes, models and infrastructure, services, and products, it will have a game-changing impact on customers. Customers will not only experience first-hand the frictionless, delightful interactions crafted via AI but also cement their loyalty to a telecom provider that helps them live better lives and that prioritizes their conveniences and preferences – all in one single window.

    Imagine the opportunities. And now, reimagine them with AI.

    Subex is at the forefront of driving AI-led transformation. To watch a demo or learn how we help you revolutionize your business with AI, reach out to us at

    hypersense@subex.com

  • Part 1: From Telcos to Tech-Cos: Carpe ‘AI’ Diem

    Part 1: From Telcos to Tech-Cos: Carpe ‘AI’ Diem

    A few years ago, if you were in India and visited any of the mom-and-pop mobile shops to buy a new SIM card, you would be presented with forms, asked to submit photocopies and a passport-size photograph, and to physically sign a document. Paperwork was then dispatched to another data entry center, an appointment date was set to verify your address, and after a few days of processing, your SIM was activated.

    Today, the entire workflow takes a mere few minutes. First, you choose your number and your package. Then, present your Aadhaar, which is scanned using its QR code, snap a picture on-the-spot to verify it is you, validate your fingerprint with a nifty little biometric machine, and receive your new SIM, which is activated and ready to go.

    At first, this scenario may appear like digitalization on steroids. But in fact, it is the organic shift of digitalization towards AI that enables intricate and differentiated experiences.

    We are all in the business of technology.

    Nearly every industry is brimming with examples of disruptive market trends driven by agile players. Think about the spate of acquisitions in the US where forward-thinking Japanese players bought out their lagging competitors who couldn’t respond to change fast enough.

    If we look at Tesla, a classic disruptor in the technology space, we can see how different their approach is. Their problem statement was not to build a car; it was to offer mobility, convenience, and safety. And they are eagerly curious to leverage the most cutting-edge technologies to achieve all of this. With the power of AI, they are pioneers in their own right in the autonomous driving and electric vehicle market and are leading the market although there were so many other companies prior to them who launched electric cars. They have also created a channel to resell their cars, unlocking a new revenue stream for the brand. Tesla is unafraid of change and is constantly reinventing itself, its products, and its models through the latest tech.

    In 2015, Anand Mahindra, Chairperson of Mahindra Group, displayed sharp foresight when he tweeted, “The age of access being offered by taxi-hailing apps like Uber and Ola is the biggest potential threat to the auto industry.”

    And he was right.

    Platforms like Uber, Lyft, Rideshare, Zoomcar, etc., have transformed the global automotive industry from being an ownership-driven one to on-demand mobility. It gave users budget-friendly travel options rather than simply buying a vehicle, thereby reaping multi-fold benefits: riders can save on down payments, EMI, parking fees, maintenance, depreciation, and more, while remaining mobile in the most convenient way. Similarly, the next generation of competition for telcos is not going to be from other telcos but from an army of digital enterprises offering a wide bouquet of services and experiences that customers are eager to lap up.

    Everybody benefits.

    It is crucial to remember that the power of AI lies not in simply digitizing a few workflows and automating processes for marginal efficiency gains. Instead, organizations realize the actual value of AI when they pan their sights outwards to visualize the entire operations landscape and reshape these, putting AI at the core.

    With AI, we are seeing a mindset of openness and sharing, which is creating profound shifts within industries and needs to be highlighted because, more than competitiveness, companies know that collaboration is what steers success today. The market share for disruptive services is too large to be monopolized by a single entity. Instead, early AI adopters are nurturing holistic digital ecosystems where AI-led innovation facilitates interoperable infrastructure, effective billing mechanisms, transparent revenue sharing agreements, strong governance frameworks, and robust security protocols.

    So, widen your AI lens.

    Some forward-thinking telecom operators have jumped on the AI bandwagon to reach more subscribers through untapped channels and accelerate onboarding through frictionless, instant, and secure workflows.

    Consider how T-Mobile is on a mission to build networks for the future. AT&T uses AI/ML to understand how climate change impacts service continuity. Telefonica leverages AI to craft immersive and intelligent living room experiences for movie watchers. Verizon 5G is grabbing the reins of Industry 4.0 by enabling smart factories through automated industrial machinery.

    Here’s an excellent place to start.

    Go back to the beginning. Relook at your business problem statements as a whole, rather than its components, and ask yourself:

    • Where do redundancies lie, and how much can we eliminate?
    • Where are inefficiencies costing us, and how can we optimize productivity?
    • What are the highest cost drivers, and where can we use AI to slash this?
    • Is there an entirely new way of performing this process that leverages everything AI stands for?

    The answers to these questions give organizations the key elements to probe AI’s value beyond incremental gains. With so much innovation happening in the telco domain – think 5G, IoT, the metaverse – telcos must push the boundaries of their imagination. Indeed, AI helps telcos do one of two things:

    1) Remain a telco that does better – They can use AI to improve the service stack, like faster broadband connectivity through 5G, and achieve incremental benefits from offerings like IoT packages to enterprises. Such point solutions will certainly deliver value like revenue and efficiency gains, albeit in a marginal manner.

    2) Transform into a tech-co that disrupts the ecosystem – They can unlock boundless opportunities to do much more than previously imagined by crafting new journeys, curating new revenue streams, and taking pole position as an enabler driver than a follower of the AI revolution.

    Which would you choose?

    Note: This is a two-part blog series. Stay tuned for the second blog that dives into how telcos can reimagine AI.

    Learn how augmented analytics can help transform your approach to enterprise AI

    Schedule a demo

  • Using KPIs to drive profitable telco-content partnerships

    Using KPIs to drive profitable telco-content partnerships

    Digital content is vogue.

    Now, more than ever, people across the globe are consuming greater quantities of different kinds of media, including news, music, books, and films, via digital channels. The shift towards digital content is guided by many factors: online content is cheaper, more varied, readily available, supports on-demand access, and provides extreme customization, to name a few.

    Underscoring the disparity between traditional and digital channels is the fact that, during the pandemic, the viewers of online TV surpassed those of broadcast TV among Gen-Z and Millennial users. In the same demographics, more listened to music streaming services instead of radio and more accessed online news instead of physical press. As global smartphone sales proliferate and network innovation and data speeds continue to improve, digital is reaching far more users in the past year than ever before. Hootsuite’s Digital 2021 Report states that since January 2020, mobile users have grown by 93 million and mobile connections by 72 million.

    Content partnerships are exploding. Here’s why.

    Telecom operators seeking to leverage the revenue advantage of customers aggressively consuming digital media want to pursue avenues to collaborate with content creators and content aggregators. The opportunity is real: A study across 5 Asian markets reveals that 42% of users feel that having a bundled media service encourages them to spend more on their mobile or fixed-line telecom plan. It is no surprise then that video streaming, OTT, and value-added service providers are in demand.

    While this is exciting for telecom, a few bottlenecks surface. For instance, how do they decide what type of content is relevant to their subscriber base? In a sea of content providers, how do they choose the most profitable ones? Finding the answers to these questions is difficult, particularly since ascertaining such criteria lies outside the scope of a telecom operator’s core operations.

    To truly tap into the potential of content-based revenue streams, telecom operators need an innovative strategy to evaluate, choose, and measure their partners.

    Using KPIs to key partner management challenges

    From a business standpoint, telecom operators want to know whether the content provider or aggregator being onboarded is legitimate, beneficial, and provides content that is relevant to the telco’s users. Two seminal questions faced by telcos are:

    1. How do I vet partners before onboarding? 

    Before determining whether the content is relevant to a user base, one should first have an idea about different content key performance indicators (KPIs) and discover data for each of these. Some parameters to consider are content relevancy, content shares, content downloads, content popularity, and user reviews.

    Such information may reside online, within different content aggregator platforms (like ratings on IMDB or likes on Spotify), within external databases, and on internal systems. The data sources are numerous, and data must be pulled from these sources and analysed to arrive at a decision. This is a tall order for just humans to do. Each KPI varies based on the type of content, making it extremely complicated to track. Above all, none of these actions lie within the domain expertise of telecom operators.

    An automated and configurable KPI-based approach to partner onboarding equips telcos with appropriate content-specific parameters for different content partners. With this, they can easily identify partnerships that will contribute to revenue growth. A useful workflow leveraging new technologies is listed below:

    • Define content-specific KPIs to assess whether the content fits within the telco’s business model and landscape
    • Capture data using APIs from distributed but relevant data sources and map these to KPIs within a matrix
    • Integrate all data on a single platform and apply analytics to arrive at a pre-boarding score
    • Assign different thresholds based on scores to automate actions such as approval, applying conditions, re-evaluation, rejection, and more
    • Configure thresholds based on scores
    • Automate reports to recommend actions, conditions, and SLAs for on-boarding

    It will not only drive faster and informed decision-making but also promote seamless onboarding for VAS and OTT partners.

    2. How do I ensure my chosen partner is beneficial?

    Measuring partner performance is vital to ensure profitability. As users search for and find the content they enjoy, they are likely to continuously engage with the telecom operator and avail or consume services, especially if the content is curated well. This means telcos must be on top of their game, constantly assessing the type of content being made available by their partners.

    Say a content aggregator has launched a new TV series, but the telco observes that viewership is scarce. Reasons could vary: The quality of content may be poor, which is the content creator’s responsibility. The price of the series could be marked higher than usual, which depends on the content aggregator. The issue of price is significant for telcos since nearly 49% of users report that they are likely to cancel their video subscription and 38% of their music subscriptions if costs increase. Similarly, the underlying issue could be slow network speeds, resulting in a poor viewing experience. This falls under the purview of the telecom provider. In each case, the resolution lies with a different entity, i.e., revising content quality guidelines, providing a pricing discount, or upping network capacity.

    To sustain profitable long-term partnerships, telecom operators need frameworks that track partner performance and encourage consistency. Here too, KPIs bring in clarity for smarter decision-making through data that is accurate, captured in real-time, and granular for intelligent insights. Coupled with new technologies, a KPI-based approach can enhance partner evaluation by helping operators:

    • Define configurable KPIs quickly for numerous content partners based on content types
    • Leverage APIs to capture data from different systems about the customer, network, and partner behaviour
    • Conduct root cause analytics to understand and resolve issues like low engagement, missed opportunities, lost sales, and more
    • Assess the success of campaigns and promotions for new releases
    • Recommend actions to course-correct and ensure high-quality content is delivered without disruption to users
    • Simplify auditing of partners and their performance, and transform this into a proactive rather than a reactive task

    Cement partner delight and operator profitability

    Telecom operators need partner lifecycle management solutions that help them handle partner interactions in a seamless and transparent manner. The need of the hour is for a partner management system that:

    • Acts as a single point of contact to manage the relationships with providers, aggregators, and merchants on a unified platform.
    • Supports partners, end-to-end, across the journey of onboarding, negotiating, contracting, reporting, assurance, billing, reconciliation, dispute management, etc.
    • Ensures accountability and visibility, both for operators as well as partners, into processes, KPIs, and SLAs, laying the foundation for rewarding relationships.
    • Provides partner enablement through a single system to easily share documents, training materials, FAQs for partner-related requests, and other information, enabling transparent collaboration across the ecosystem.

    Integrated partner lifecycle management empowers telecom providers to find the right partners, track pricing models, assess content KPIs, and evaluate partner performance without shifting their focus from the core business. It also provides insights that can drive success in other functions such as revenue assurance, sales enablement, and network planning.

    Learn to Enable end-to-end partner lifecycle management for profitable partnerships

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  • Part 1: From Telcos to Tech-Cos: Carpe ‘AI’ Diem

    A few years ago, if you were in India and visited any of the mom-and-pop mobile shops to buy a new SIM card, you would be presented with forms, asked to submit photocopies and a passport-size photograph, and to physically sign a document. Paperwork was then dispatched to another data entry center, an appointment date was set to verify your address, and after a few days of processing, your SIM was activated.

    Today, the entire workflow takes a mere few minutes. First, you choose your number and your package. Then, present your Aadhaar, which is scanned using its QR code, snap a picture on-the-spot to verify it is you, validate your fingerprint with a nifty little biometric machine, and receive your new SIM, which is activated and ready to go.

    At first, this scenario may appear like digitalization on steroids. But in fact, it is the organic shift of digitalization towards AI that enables intricate and differentiated experiences.

    We are all in the business of technology.

    Nearly every industry is brimming with examples of disruptive market trends driven by agile players. Think about the spate of acquisitions in the US where forward-thinking Japanese players bought out their lagging competitors who couldn’t respond to change fast enough.

    If we look at Tesla, a classic disruptor in the technology space, we can see how different their approach is. Their problem statement was not to build a car; it was to offer mobility, convenience, and safety. And they are eagerly curious to leverage the most cutting-edge technologies to achieve all of this. With the power of AI, they are pioneers in their own right in the autonomous driving and electric vehicle market and are leading the market although there were so many other companies prior to them who launched electric cars. They have also created a channel to resell their cars, unlocking a new revenue stream for the brand. Tesla is unafraid of change and is constantly reinventing itself, its products, and its models through the latest tech.

    In 2015, Anand Mahindra, Chairperson of Mahindra Group, displayed sharp foresight when he tweeted, “The age of access being offered by taxi-hailing apps like Uber and Ola is the biggest potential threat to the auto industry.”

    And he was right.

    Platforms like Uber, Lyft, Rideshare, Zoomcar, etc., have transformed the global automotive industry from being an ownership-driven one to on-demand mobility. It gave users budget-friendly travel options rather than simply buying a vehicle, thereby reaping multi-fold benefits: riders can save on down payments, EMI, parking fees, maintenance, depreciation, and more, while remaining mobile in the most convenient way. Similarly, the next generation of competition for telcos is not going to be from other telcos but from an army of digital enterprises offering a wide bouquet of services and experiences that customers are eager to lap up.

    Everybody benefits.

    It is crucial to remember that the power of AI lies not in simply digitizing a few workflows and automating processes for marginal efficiency gains. Instead, organizations realize the actual value of AI when they pan their sights outwards to visualize the entire operations landscape and reshape these, putting AI at the core.

    With AI, we are seeing a mindset of openness and sharing, which is creating profound shifts within industries and needs to be highlighted because, more than competitiveness, companies know that collaboration is what steers success today. The market share for disruptive services is too large to be monopolized by a single entity. Instead, early AI adopters are nurturing holistic digital ecosystems where AI-led innovation facilitates interoperable infrastructure, effective billing mechanisms, transparent revenue sharing agreements, strong governance frameworks, and robust security protocols.

    So, widen your AI lens.

    Some forward-thinking telecom operators have jumped on the AI bandwagon to reach more subscribers through untapped channels and accelerate onboarding through frictionless, instant, and secure workflows.

    Consider how T-Mobile is on a mission to build networks for the future. AT&T uses AI/ML to understand how climate change impacts service continuity. Telefonica leverages AI to craft immersive and intelligent living room experiences for movie watchers. Verizon 5G is grabbing the reins of Industry 4.0 by enabling smart factories through automated industrial machinery.

    The use cases keep growing: AI technologies like natural language processing, face trace, liveness detection, and face match can greatly streamline governance by instantly validating ID proof against applicants and cross-checking authenticity. ML algorithms can mine data to understand customer preferences and personalize offers within seconds.

    Here’s an excellent place to start.

    Go back to the beginning. Relook at your business problem statements as a whole, rather than its components, and ask yourself:

    • Where do redundancies lie, and how much can we eliminate?
    • Where are inefficiencies costing us, and how can we optimize productivity?
    • What are the highest cost drivers, and where can we use AI to slash this?
    • Is there an entirely new way of performing this process that leverages everything AI stands for?

    The answers to these questions give organizations the key elements to probe AI’s value beyond incremental gains. With so much innovation happening in the telco domain – think 5G, IoT, the metaverse – telcos must push the boundaries of their imagination. Indeed, AI helps telcos do one of two things:

    1) Remain a telco that does better – They can use AI to improve the service stack, like faster broadband connectivity through 5G, and achieve incremental benefits from offerings like IoT packages to enterprises. Such point solutions will certainly deliver value like revenue and efficiency gains, albeit in a marginal manner.

    2) Transform into a tech-co that disrupts the ecosystem – They can unlock boundless opportunities to do much more than previously imagined by crafting new journeys, curating new revenue streams, and taking pole position as an enabler driver than a follower of the AI revolution.

    Which would you choose?

    Note: This is a two-part blog series. Stay tuned for the second blog that dives into how telcos can reimagine AI.

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  • Software License Management: The 8 key ingredients for managing software licenses for the telecom industry

    Software License Management: The 8 key ingredients for managing software licenses for the telecom industry

    In today’s telecom world, organizations are heavily reliant on software solutions for numerous functions, including task-critical ones. As a result, software licensing can be a significant budget entity for many organizations. Effective license management is essential to preventing inaccurate tracking of software licenses and usage measurement issues that can cause budget discrepancies.

    In almost all cases, the software is sold by licensing, whether it be a perpetual license to use the software or a subscription settled monthly or yearly that must be renewed continually. To ensure that you are utilizing every penny spent out of your software assets, the first thing to do is to understand the types of licensing agreements and plan the license management accordingly.

    This is where Software license management (SLM) comes in. Software license management refers to all organizational aspects of deploying and maintaining your organization’s software assets. It is a part of the broader software asset management category.

    Given the large share spent on software licenses, an exceptional benefit of SLM is the revenue it can save you by identifying unnecessary or unused/underused software. Paying for such software can stack up to a sizable sum for each user or device covered by an unused solution. SLM enables you to track all software purchases and audit their usage, or lack thereof, in the case of unused paid subscriptions.

    Another benefit of SLM that can help in even more significant financial savings is that it enables enforcing compliance with End-User License Agreements (EULA). Any device running unlicensed software reveals you to potential financial penalties and legal issues in most circumstances.

    When following your software licenses, it is vital to know how the latest technology impacts software usage and policies. With 5G and, thereby, artificial intelligence (AI), augmented reality (AR), machine learning (ML), and the Internet of Things (IoT) picking up pace in recent years, software licensing has had to adjust to the advancements introduced by these developments.

    The extensive use of automation powered by AI and ML has impacted SLM by enabling the automatic functioning of many of the processes. This includes overlooking what programs are being used, how they are being used, and setting up control protocols to limit their usage to authorized individuals and roles. These tools can also be used in the maintenance of software to make it easier to detect violations of EULA.

    IoT devices are now present at all business and consumer levels and functions, including telecom. Observably, the SLM implications of these devices can be tricky, and the software underlying them can be challenging to manage using traditional SLM tools and procedures. It’s important to track new processes for applying SLM techniques to IoT devices to optimize your ability to utilize them. Proactive SLM allows the improvement of your IT efforts. It provides the possibility to lower costs and boost your ability to react to changing business conditions by drawing the maximum advantage of the capabilities of your software rapidly.

    As we have seen, managing your software licenses is essential to avoid the negative results associated with non-compliance. The following are points to help your telecom business to manage software licenses:

    Document software management policies

    SLM records and stores your software management policies to manage and serve when required to avoid costly surprises come audit time.

    Usage governance procedures

    Establishing controls for managing software usage across the organization and groups of workspaces is a breeze with SLM. It also ensures that only authorized users can download and use the software they are authorized to use. These management controls are critical in an era where users can effortlessly access the software at work or home on various devices. The procedures of usage of software policies in all telecom spaces should be tied to your usage governance utility to effectively onboard and offboard employees via provisioning automation.

    Software lifecycle management

    Special care must be undertaken to manage all aspects of the software lifecycle, including renewing licenses, updating information, and communicating usage parameters to employees. With SLM, it can be done efficiently.

    Usage monitoring

    It is necessary to constantly monitor which programs are present on your network, how they are being used, and who is using them to ensure that your authorization policies are working as planned and that the correct solutions are being applied for desired purposes. With SLM integrated, it is still possible to use automated and manual auditing when needed.

    Automated updating checks

    Automated discovery of software versions is available with SLM, enabling you to operate on the most recent version of any installed programs consistently.

    Reclaiming procedures

    Regularly uninstalling software that has been idle for a certain prescribed period and return it to stock for future reuse or cancellation if suitable.

    Track contracts

    SLM analyzes contract databases and procurement records to enable easy compliance with contractual conditions and viewing important contract data such as license type, number of authorized users, and expiration dates with fewer steps than manually looking through them.

    Employ license management automation

    Software License Management solutions can help optimize your license management by developing vendor licensing profiles you can use to automate the process of moderating your license status to installed software. This can help the efficiency of license management, especially in preparing for a true-up or other large-scale audits.

    Establish and track software management objectives

    To measure the effectiveness of your SLM efforts or select licenses for cost-saving objectives and track your performance about goals over time that can be achieved with proper SLM.

    With a substantial portion of software costs resulting from inadequate software management, the case for software licensing management is a strong one. According to research from Gartner, many organizations can ameliorate software spending by as much as 30% via software license optimization via best practices. Besides revenue optimization, effective SLM can generate revenue, and there are also efficiency gains to be experienced by making better use of the software your organization has acquired.

    SLM can benefit telecom organizations by helping them effectively use their software to quickly react and adapt to changing market conditions, optimize operations, and stay in compliance with EULA. At a minimum, SLM can help you track and optimize your software policies to help your managers acquire and use the tools at the right time.

    Why is Network License Management crucial for Telecom Operators?

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    References:

    https://www.yumpu.com/en/document/view/37782291/software-licensing-in-telecom-industry-an-analysis-softsummit

    https://www.bmc.com/blogs/software-license-management/

    https://www.dell.com/en-us/blog/a-fundamental-shift-in-how-telecom-networks-are-built/

    https://www.researchgate.net/publication/260591298_Licensing_Models_and_their_Impact_on_the_Telecom_Software_Industry

    https://www.cisco.com/c/en/us/buy/enterprise-agreement/resources/what-is-software-license-management.html#~conclusion

  • Gartner Recognizes HyperSense for AI and Data Science

    Gartner Recognizes HyperSense for AI and Data Science

    Gartner listed Subex as a representative vendor for multi-persona Data Science and Machine Learning (DSML) platforms in its recently published ‘Market Guide for Multipersona Data Science and Machine Learning Platforms’ report.

    The representative vendors were evaluated on technical parameters such as: data access, exploration, visualization, model development, and advanced analytics. Other aspects such as user interface modalities, collaboration, infrastructure, performance, and scalability were also considered.

    About the report

    The Market Guide is the latest report published by Gartner in the area of Data Science and Machine platforms, replacing the Magic Quadrant for the same category. The report highlights the rising relevance of data science and machine learning due to data democratization and looks into the rising prominence of AI and data science as organizations start executing their AI strategies. It provides an in-depth view of the DSML market, key recommendations for data and analytics leaders, and touches upon the questions addressed by Data Science and Machine Learning platforms. Key takeaways are:

    • DSML platforms offer comprehensive analytics and business intelligence coverage through descriptive, prescriptive, and predictive insights.
    • These are evolving into a multi-disciplinary approach by enabling meaningful collaboration between advanced data scientists, citizen data scientists, business leaders, and enterprise teams.
    • Strong governance is needed, considering the prominent role Data Science and Machine Learning will play in automated decision-making.

    The Significance of DSML platforms

    The rate at which data is generated requires high computing and intelligent processing power to make sense of information at a speed that can deliver value to businesses. Right now, organizations use several siloed applications to peer into different datasets (that seem most relevant to the specific function) and get insights. However, the power of data lies in its gestalt, and this is why enterprises need a centralized and powerful platform that ingests diverse, unstructured data in an automated manner. Furthermore, as technology investments in 5G, IoT, AR/VR, etc., continue to grow, organizations turn to AI models to handle exploding data volumes. However, moving from data democratization to AI orchestration is a task typically done by advanced data scientists, who are in short supply.

    Yet, AI and data science are in high demand. Gartner predicts that the AI and data science market will exceed US $10 billion by 2025. Early adopters of AI are already running pilot programs while those still in the planning phases want simpler implementation methods. Thus, the onus falls on Data Science and Machine Learning platforms to drive this growth.

    Data Science and Machine Learning platforms, in their no-code automation way, allow business users with good digital understanding to double up as citizen data scientists and start using AI/ML models for business needs. AI-driven decision analytics coupled with strong orchestration makes AI accessible and scalable across business units and organizational levels. In a nutshell, Data Science and Machine Learning platforms help organizations keen on implementing AI to create a useable talent pool, demonstrate early wins, and scale and federate AI-led initiatives.

    The underlying lever of Data Science and Machine Learning platforms is that they augment user support through data democratization. What sets such platforms apart is their ability to deliver and scale enterprise AI through well-governed, risk-proofed, and responsible AI/ML models powered by data science. They empower organizations by:

    • Providing access to many user groups that may be skilled with digital technology and can now create models that use data science, analytics, and intelligence.
    • Automating AI pipelines in a user-friendly and no-code way for improved productivity and efficiency.
    • Accelerating time to value through pre-built use cases and models that are performant, scalable, and secure, thereby increasing adoption.

    How to make better decisions with AI through HyperSense

    HyperSense AI is a cloud-native and SaaS-based platform that democratizes and orchestrates AI across the entire data value chain. Through HyperSense AI, business users can easily unify data from disparate sources, automate tedious and complex data science processes, and convert data into insights through auto visualization. These insights can be translated across organizational hierarchies so leaders can make the best decisions for their teams based on real-time, reliable data.

    With a host of pre-built use cases, HyperSense AI is composable and extremely reusable. The platform has in-built AutoML to automate many data science workflows and MLOps to foster impactful collaboration between enterprise teams.

    The Gartner feature comes on the heels of Subex being named a representative vendor in Gartner’s Market Guide on AI in CSP Customer and Business Operations through HyperSense AI.

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  • AI-First Fraud Management System: Next-Gen Reinforcements to Fight Fraud

    AI-First Fraud Management System: Next-Gen Reinforcements to Fight Fraud

    Telecom is buzzing with new trends that promise to disrupt its current role as a network provider. To illustrate, 5G will turn out US $13.2 trillion in global economic value by 2035, brought on by enhanced mobile broadband, massive machine-type communication, and ultra-reliable low latency networks. The metaverse is emerging as an alternate immersive digital world that merges with the physical one through augmented, virtual, and mixed reality experiences. It could spell new opportunities for telcos to collaborate with hyper-scalers for seamless service delivery. Meanwhile, developers excitedly look to using 5G’s low latency features to enable edge computing, spawning numerous use cases for telcos around autonomous transport, virtual gaming, predictive asset maintenance, and smart grids.

    The time is now for telcos to start preparing for a future where their roles shift from infrastructure and network providers to strategic ecosystem players that offer vital services and solutions.

    Where opportunity lies, so does risk

    The emergence of new technologies also throws open the CSPs’ scope of work into an infinite expanse ranging from monitoring network security and tearing down emergent cyber threats to evaluating new products, services, partners, etc. In the new world, risk professionals may have to refocus their sights on:

    • Understanding implicit patterns within data to profile risk so as to protect company investments. High variability in data makes it difficult to arrive at the right decisions. Risk professionals must consider variability metrics such as deviation, ranges, and variances when dealing with multi-dimensional data and seasonality trends.
    • Processing a wide variety of data, such as streaming data, data lakes, and protocol data, that are saved in unstructured and semi-structured formats.
    • Checking data veracity, such as where it is collected from and the reliability of source datasets, means spending effort to check if data is useable for risk prediction models.
    • Dealing with velocity or high-speed data to automate decisions within milliseconds, such as denylisting a blocked call or alerting on fake sales and campaigns.
    • Exploding data volumes that need sophisticated tools to handle signaling data, behavioral profiling, partner tracking, transaction monitoring, and more
    • Visualizing data using modern techniques so they can unlock value and glean useful insights quickly is a challenge considering the dynamic way data behaves.

    Three must-have parameters in AI-led fraud management system

    Considering the multi-faceted data that risk professionals must handle, they need sophisticated tools to deal with different risk types, including fraud, AML, data theft, and security breaches. Unfortunately, traditional techniques falter at handling the fluid behavior of today’s data, and this is where machine learning plays a key role.

    ML models can mine insights, offer interpretability of results, and provide recommendations. For instance, in some cases, users may very well find that the power of AI is best delivered when accessible at the edge in what is known as edge AI. ML also powers use cases of predictive analytics, network security, and more. From a fraud perspective, it can boost the ability of risk professionals to detect fake caller profiles, illegal access, and incidents of different fraud types, including IRSF, CLI spoofing, etc., through behavioral monitoring of global CSP networks.

    When evaluating the business case of investing in an AI-first approach to fraud management systems (FMS), telecom operators should adopt a long-term view of what AI delivers. Here are three aspects that AI-led Fraud Management System must cater to and three ways it reinforces your existing fraud management strategy:

    • Self-serve – Risk professionals must make faster decisions to keep pace with the business. For this, they need agile and reskilled teams. AI-based fraud management systems give users agility. It leverages APIs to integrate with any source dataset and feed information into risk decision engines. When risk scores are hosted through APIs, it remains available for other teams to access as a microservice, heightening the reusability of AI in a self-serve manner. Moreover, AI frees resources from repetitive tasks through automation pipelines that work with predictable outputs. It also supports various analytics types, such as statistical, behavioral, predictive, and protocol analysis. Adopting AI itself drives a culture of re-skilling as risk management teams must improve their data literacy and create citizen data scientists who are proficient enough to work with AI models, generate output, and translate the results into business outcomes for faster decision-making on new products and service launches.
    • Explainability and recommendations – AI-powered decision-making is crucial for reliable and effective fraud management. By providing the explainability of AI logic, AI-led FMS enables model accuracy, fairness, and transparency. It helps users trust model outcomes and leverage its recommendations with confidence. Moreover, an intuitive user interface with data workflows and a pipeline for risk identification, investigation, and actioning will further enrich the user experience.
    • Technology – Cloud-native architecture enables scalability, security, and interoperability. New features, model enhancements, and upgrades can be easily deployed to keep the system resilient and relevant. Additionally, building the tech stack as a containerized model can support the niche requirements of CSPs at lower TCO.

    A holistic risk assessment program outfitted with the right tools and processes is key to survival in this disruptive age. Subex’s AI-First fraud management, powered by HyperSense, leverages AI in every step of the fraud management process to enhance accuracy, coverage, and time-to-market and also to enable using AI in a sustained manner. It has over 350 fraud use cases supporting risk professionals in delivering next-gen digital services.

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  • Peeling away the layers of the metaverse

    Peeling away the layers of the metaverse

    The metaverse will feel like a hybrid of today’s online social experiences, sometimes expanded into three dimensions or projected into the physical world. It will let you share immersive experiences with other people even when you can’t be together—and do things together you couldn’t do in the physical world.

    The above is how Facebook, now Meta, defines the metaverse.

    In simpler words, the Internet has evolved over the years, growing in sophistication, connections, and technologies. Its upcoming evolution could spawn a world where users can drive deeper relationships, meshed within the economic implications. This world is what we understand as the ‘metaverse.’

    The actual term ‘metaverse’ was coined by Neal Stephenson in his science fiction book Snow Crash, published in 1992, to reference a 3D world where humans could interact using avatars. Facebook is one company building a metaverse, as are other giants such as Decentraland and The Sandbox.

    While still an ephemeral concept, the metaverse is talked about excitedly in some circles with its potential to leverage 5G, VR, AR, and AI in a much more profound manner. Some reports estimate that the metaverse market will surpass US $1.5 trillion by 2030. This is apart from the US $100 billion market opportunity of metaverse-friendly gadgets and wearables. Many are making investments to understand this space and prepare for the possible opportunities it unlocks. The use cases for gamers are already exploding, and this will most likely be the first frontier for the metaverse.

    What can one do in the metaverse?

    Borne from the evolved applications of AR and VR, the metaverse represents a kind of converged virtual 3D world that integrates aspects of the physical world and other digital interactions. Users have avatars that can execute actions – real and imagined.

    Since the pandemic, much of user experiences and lives have shifted online, giving impetus to the concept of a metaverse. Here are some possible things you can do in a metaverse:

    • Create compelling 3D spaces to showcase new products, allowing customers to experience them through AR/VR devices. Nike has already invested in Nikeland, its virtual shopfront that sells digital sports merchandise and sports fashion for avatars of users in the metaverse.
    • Build interesting avatars of users based on their different personas and metaverse interactions.
    • Plan trade shows, concerts, and art festivals where businesses and customers can interact and even execute deals. For instance, Warner Music Group is partnering with The Sandbox to develop a hybrid musical theme park and concert hall to organize immersive music experiences hosted by top celebrities like Ed Sheeran, Bruno Mars, Cardi B, and more.
    • Create next-gen remote workplaces where employees can punch in, attend meetings and training, and collaborate and converse with other meta-employees. For example, a Danish architecture company has designed a virtual office on the Decentraland metaverse for employees at Vice Media Group. Employees can work out of this new ‘headquarters’, meet meta-mentors, and collaborate with their colleagues across the globe.
    • Develop meta-enabled schools that align with recognized syllabi and curricula whereby students and teachers can extend the concept of online learning beyond eLearning apps by providing immersive remote education. A Florida-based school called The Optima Classical Academy is building a metaverse school where over 1000 students can choose their courses, attend live VR-based tutorial sessions using issued Oculus headsets, and experience subjects like world history and astronomy like never before.
    • Buy/rent homes, stores, and property, build a community of neighbors, and transact and work in the metaverse. For example, a crypto investor bought virtual estate worth US $2.4 million in cryptocurrency in Decentraland, the most expensive purchase recorded by the metaverse platform.

    What makes the metaverse unique is that, unlike most virtual reality worlds that are static, the metaverse keeps changing. Each interaction creates data that can be leveraged by businesses and organizations to evolve the metaverse and fine-tune each experience. The applications of AR and VR in the metaverse are unlimited, and many organizations are exploring how they can create new revenue streams or enhance customer experiences through the metaverse. Considering that Facebook already has 2.8 million users globally, imagine the depth of opportunities possible if all of these users could engage in the metaverse and interact in real-time, virtually.

    The role of 5G in the metaverse

    Building these complicated spaces in the metaverse will require unprecedented download and upload speeds and robust infrastructure, most of which may center on telecom networks. We can expect to see AR/VR applications maturing to include the sense of touch, smell, sound, and more. 5G is the only network technology that can support the massive digital files needed to create such an experience and the speeds at which information and transactions flow through the metaverse.

    Thus, as metaverse-enabled technologies evolve, mobile operators have a critical role to play through their investments in 5G, multi-access edge computing, and network slicing. Many are already investing in high-bandwidth and low-latency networks for countless real-time use cases across gaming, surveillance, defense, etc. Looking ahead, they ought to consider building viable business models that allow them to go beyond merely provisioning infrastructure to provide holistic products that can be consumed by metaverse users, such as fraud management and digital identity solutions (for businesses) and wearables and digital avatars (for users).

    A prelude to the risks in the metaverse

    However, risks lurk behind the shadows. Termed as a potential “scammer’s paradise,” the metaverse is nascent and heavily unregulated. As a result, fraud, piracy, crime, and governance issues loom large. For instance, cryptocurrency may very well be the most popular form of currency for users to transact in the metaverse, despite cryptocurrency crime reached an all-time high of US $14 billion in 2021. Thus, securing the metaverse needs to be a top priority for telecom providers if they are to build customer trust.

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